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Maximum likelihood estimation for hidden semi-Markov models
Comptes Rendus. Mathématique, 2006 In this Note we consider a discrete-time hidden semi-Markov model and we prove that the nonparametric maximum likelihood estimators for the characteristics of such a model have nice asymptotic properties, namely consistency and asymptotic normality.
Barbu, Vlad, Limnios, Nikolaos
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Finite-Time Asynchronous H∞ Control for Non-Homogeneous Hidden Semi-Markov Jump Systems
MathematicsThis article explores the finite-time control problem associated with a specific category of non-homogeneous hidden semi-Markov jump systems. Firstly, a hidden semi-Markov model is designed to characterize the asynchronous interactions that occur between
Qian Wang +3 more
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Movement Ecology, 2023 Background State-space models, such as Hidden Markov Models (HMMs), are increasingly used to classify animal tracks into behavioural states. Typically, step length and turning angles of successive locations are used to infer where and when an animal is ...
Sarah Saldanha +3 more
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Semi-Supervised Learning of Hidden Markov Models via a Homotopy Method [PDF]
, 2006 Hidden Markov model (HMM) classifier design is considered for analysis of sequential data, incorporating both labeled and unlabeled data for training; the balance between labeled and unlabeled data is controlled by an allocation parameter lambda in [0, 1)
Carin, Lawrence +2 more
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Bootstrapping Information Extraction from Field Books [PDF]
, 2008 We present two machine learning approaches to information extraction from semi-structured documents that can be used if no annotated training data are available, but there does exist a database filled with information derived from the type of documents ...
Caroline Sporleder, Er Canisius
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A Logical Hierarchical Hidden Semi-Markov Model for Team Intention Recognition
Discrete Dynamics in Nature and Society, 2015 Intention recognition is significant in many applications. In this paper, we focus on team intention recognition, which identifies the intention of each team member and the team working mode.
Shi-guang Yue +3 more
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hmmTMB: Hidden Markov Models with Flexible Covariate Effects in R
Journal of Statistical SoftwareHidden Markov models (HMMs) are widely applied in studies where a discrete-valued process of interest is observed indirectly. They have for example been used to model behavior from human and animal tracking data, disease status from medical data, and ...
Théo Michelot
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, 2010 Large trades in a financial market are usually split into smaller parts and traded incrementally over extended periods of time. We address these large trades as hidden orders.
Lillo, Fabrizio +2 more
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Dirichlet Posterior Sampling with Truncated Multinomial Likelihoods [PDF]
, 2012 We consider the problem of drawing samples from posterior distributions formed under a Dirichlet prior and a truncated multinomial likelihood, by which we mean a Multinomial likelihood function where we condition on one or more counts being zero a priori.
Johnson, Matthew James, Willsky, Alan S.
core
A decision-theoretic approach for segmental classification
, 2013 This paper is concerned with statistical methods for the segmental classification of linear sequence data where the task is to segment and classify the data according to an underlying hidden discrete state sequence.
Holmes, Christopher C., Yau, Christopher
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